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  • 标题:Optimal Path of Internet of Things Service in Supply Chain Management Based on Machine Learning Algorithms
  • 本地全文:下载
  • 作者:Jing Li ; Ruifeng Zhang ; Yanfeng Jin
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/4844993
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:With the development of global economic integration, the scale of supply chain network is becoming larger and larger. The research on the benefits of supply chain network under the Internet of Things technology is a new interdisciplinary research issue. Starting from the complexity and evolution of supply chain network, based on machine learning algorithms, this study analyses the service modes of the Internet of Things for supply chain enterprises, such as RFID technology, EDI technology, and enterprise resource planning ERP. Finally, by analyzing the degree of application of the Internet of Things in different industries, the manufacturing industry is selected for simulation. It is found that the introduction of the Internet of Things is conducive to speeding up the evolution of enterprise supply chain. Thus, the horizontal integration of the optimized path supply chain can effectively improve the overall profits of enterprises and provide theoretical support for the Internet of Things service supply chain.
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